Self-monitoring time series database system that enforces usage policies

ABSTRACT

A self-monitoring time series database system which enforces usage policies is described. A time series database system receives an alert trigger condition for a system user, wherein the system user is associated with multiple time series data points corresponding to multiple subsystems of the time series database system. The time series database system aggregates the multiple time series data points in an internal time series data point, which is internal to the time series database system, associated with the system user. The time series database system evaluates whether the internal time series data point associated with the system user meets the alert trigger condition. The time series database system reduces a level of access by the system user to the time series database system in response to an evaluation that the internal time series data point associated with the system user meets the alert trigger condition.

COPYRIGHT NOTICE

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BACKGROUND

The subject matter discussed in the background section should not beassumed to be prior art merely as a result of its mention in thebackground section. Similarly, a problem mentioned in the backgroundsection or associated with the subject matter of the background sectionshould not be assumed to have been previously recognized in the priorart. The subject matter in the background section merely representsdifferent approaches, which in and of themselves may also be inventions.

Time series data is a sequence of data points, typically consisting ofsuccessive measurements made over a time interval. Examples of timeseries data are ocean tides, counts of sunspots, and the daily closingvalue of the Dow Jones Industrial Average. Time series data isfrequently plotted via line charts. Many domains of applied science andengineering which involve temporal measurements use time series data.Time series data analysis comprises methods for analyzing time seriesdata in order to extract meaningful statistics and other characteristicsof the data. Time series data forecasting is the use of a model topredict future values based on previously observed values. A time seriesdatabase is a computer system that is optimized for handling time seriesdata. In some fields, time series data is called a profile, a curve, ora trace. Despite the disparate names, many of the same mathematicaloperations, queries, or database transactions are useful for analyzingeach of these time series data types. The implementation of acomputerized database system that can correctly, reliably, andefficiently implement these operations must be specialized for timeseries data.

BRIEF DESCRIPTION OF THE DRAWINGS

In the following drawings like reference numbers are used to refer tolike elements. Although the following figures depict various examples,the one or more implementations are not limited to the examples depictedin the figures.

FIG. 1 is an operational flow diagram illustrating a high level overviewof a method for a self-monitoring time series database system whichenforces usage policies, in an embodiment;

FIG. 2 is an operational flow diagram illustrating a high level overviewof a method for a self-monitoring time series database system whichenforces usage policies based on monitoring rate of change, in anembodiment;

FIG. 3 illustrates a block diagram of an example of an environmentwherein an on-demand database service might be used; and

FIG. 4 illustrates a block diagram of an embodiment of elements of FIG.3 and various possible interconnections between these elements.

DETAILED DESCRIPTION General Overview

Systems and methods are provided for a self-monitoring time seriesdatabase system which enforces usage policies. As used herein, the termmulti-tenant database system refers to those systems in which variouselements of hardware and software of the database system may be sharedby one or more customers. For example, a given application server maysimultaneously process requests for a great number of customers, and agiven database table may store rows for a potentially much greaternumber of customers. As used herein, the term query plan refers to a setof steps used to access information in a database system. Next, methodsand mechanisms for a self-monitoring time series database system whichenforces usage policies will be described with reference to exampleembodiments. The following detailed description will first describe amethod for a self-monitoring time series database system which enforcesusage policies.

In accordance with embodiments described herein, there are providedmethods and systems for a self-monitoring time series database systemwhich enforces usage policies. One skilled in the art will understandthat a time series database system is a computer system that isoptimized for handling time series data, but may be able to handle otherdata as well. A time series database system receives an alert triggercondition for a system user, wherein the system user is associated withmultiple time series data points corresponding to multiple subsystems ofthe time series database system. The time series database systemaggregates the multiple time series data points in an internal timeseries data point, which is internal to the time series database system,associated with the system user. The time series database systemevaluates whether the internal time series data point associated withthe system user meets the alert trigger condition. The time seriesdatabase system reduces a level of access by the system user to the timeseries database system in response to an evaluation that the internaltime series data point associated with the system user meets the alerttrigger condition.

For example, a system administrator for a time series database systemsubmits an alert trigger condition of 1,500 web service API calls perminute for the system user named John Smith for when Smith uses acluster of 5 computer nodes, and the time series database systemidentifies 5 time series data points associated with the system userJohn Smith, which indicate Smith's web service API calls for the 5computer nodes within the time series database system. The time seriesdatabase system: 1) creates a global counter, 2) aggregates the 5 timeseries data points which indicate Smith's web service API calls for the5 computer nodes into the global counter, 3) disables subsystemaggregation to the global counter, 3) copies the aggregated value of1,600 in the global counter to a data structure, 4) resets the globalcounter, enables subsystem aggregation to the global counter, and 5)persists the aggregated value of 1,600 in the data structure to aninternal time series data point for the system user John Smith in thetime series database system.

The time series database system evaluates whether the internal timeseries data point aggregating the 5 time series data points, whichindicate Smith's 1,600 web service API calls for the 5 computer nodes,meets the alert trigger condition of 1,500 web service API calls perminute for the time series database system. The time series databasesystem temporarily suspends John Smith's access to the time seriesdatabase system because the evaluation of the internal time series datapoint indicates that Smith's 1,600 web service API calls for the 5computer nodes meets the alert trigger condition of 1,500 web serviceAPI calls per minute for the time series database system. Theself-monitoring time series database system that enforces usage policiescan selectively reduce the access of a user who may be abusing ormisusing the system, thereby preserving normal system access for theother users, even if the system user is not exceeding any thresholds forsystem subcomponents.

While one or more implementations and techniques are described withreference to an embodiment in which a self-monitoring time seriesdatabase system which enforces usage policies is implemented in a systemhaving an application server providing a front end for an on-demanddatabase service capable of supporting multiple tenants, the one or moreimplementations and techniques are not limited to multi-tenant databasesnor deployment on application servers. Embodiments may be practicedusing other database architectures, i.e., ORACLE®, DB2® by IBM and thelike without departing from the scope of the embodiments claimed.

Any of the embodiments described herein may be used alone or togetherwith one another in any combination. The one or more implementationsencompassed within this specification may also include embodiments thatare only partially mentioned or alluded to or are not mentioned oralluded to at all in this brief summary or in the abstract. Althoughvarious embodiments may have been motivated by various deficiencies withthe prior art, which may be discussed or alluded to in one or moreplaces in the specification, the embodiments do not necessarily addressany of these deficiencies. In other words, different embodiments mayaddress different deficiencies that may be discussed in thespecification. Some embodiments may only partially address somedeficiencies or just one deficiency that may be discussed in thespecification, and some embodiments may not address any of thesedeficiencies.

FIG. 1 is an operational flow diagram illustrating a high level overviewof a method 100 for a self-monitoring time series database system thatenforces usage policies. A time series database system receives an alerttrigger condition for a system user, wherein the system user isassociated with multiple time series data points corresponding tomultiple subsystems of the time series database system, block 102. Forexample and without limitation, this can include a system administratorfor a time series database system submitting an alert trigger conditionof 1,500 web service API calls per minute for the system user named JohnSmith for when Smith uses a cluster of 5 computer nodes, and alerttrigger conditions of 500 web service API calls per minute for Smith forwhen he uses each of the 5 computer nodes. Continuing this example, thetime series database system identifies 5 time series data pointsassociated with the system user John Smith, which indicate Smith's webservice API calls for the 5 computer nodes within the time seriesdatabase system.

Although the foregoing example describes the time series database systemidentifying the multiple time series data points that are associatedwith the alert trigger condition, a system administrator may identifythe multiple time series data points that are associated with the alerttrigger condition when submitting the alert trigger condition. Whilethis example describes the time series database system receiving andprocessing a single alert trigger condition for one system user who isassociated with multiple time series data points corresponding tomultiple subsystems of the time series database system, the time seriesdatabase system may receive and process any number of alert triggerconditions for any number of system users. Even though this exampledescribes the time series database system receiving an alert triggercondition for a system user from a system administrator, the time seriesdatabase may also receive an alert trigger condition for a system userfrom a configuration file.

For example, upon startup, the time series database system initiallyreceives an alert trigger condition of 2,000 web service API calls perminute for each system user from a configuration file that waspre-configured prior to startup of the time series database system.Continuing this example, after months of operation, the time seriesdatabase system receives an alert trigger condition of 1,500 web serviceAPI calls per minute for each system user from a system administratorwho decided that the alert trigger condition of 2,000 web service APIcalls per minute for each system user was set too high for responding tothe corresponding alert notification in a timely manner.

In another example, the time series database system receives an alerttrigger condition of 1,500 web service API calls per minute for JohnSmith from a system administrator who submitted an alert triggercondition of 2,000 web service API calls per minute for Mary Jonesbecause Jones pays more for system access than Smith pays for systemaccess.

After receiving the alert trigger condition for a system user who isassociated with multiple time series data points, the time seriesdatabase system aggregates the multiple time series data points in aninternal time series data point, which is internal to the time seriesdatabase system, associated with the system user, block 104. By way ofexample and without limitation, this can include the time seriesdatabase system: 1) creating a global counter, aggregating the 5 timeseries data points that indicate Smith's web service API calls for the 5computer nodes into the global counter, 2) disabling subsystemaggregation to the global counter, 3) copying the aggregated value of1,600 in the global counter to a temporary data structure, 4) resettingthe global counter to zero, 5) enabling subsystem aggregation to theglobal counter, and 6) persisting the aggregated value of 1,600 in thetemporary data structure to an internal time series data point for thesystem user John Smith in the time series database system.

Although this example describes the time series database systemaggregating a single internal time series data point for one system userfrom multiple corresponding time series data points, the time seriesdatabase system may aggregate any number of internal time series datapoints for any number of system users from their multiple correspondingtime series data points. While this example describes the time seriesdatabase system copying the aggregated value in the global counter to atemporary data structure, and then persisting the aggregated value inthe temporary data structure to an internal time series data point for asystem user, the time series database system may copy the aggregatedvalue in the global counter to an internal time series data point forthe system user.

After aggregating the multiple time series data points in the internaltime series data point for a system user, the time series databasesystem evaluates whether the internal time series data point associatedwith the system user meets the alert trigger condition, block 106. Inembodiments, this can include the time series database system evaluatingwhether the internal time series data point aggregating the 5 timeseries data points that indicate Smith's 1,600 web service API calls forthe 5 computer nodes, meets the alert trigger condition of 1,500 webservice API calls per minute for the time series database system.Although this example describes an alert trigger condition for a systemuser based on an internal time series data point associated with thesystem user meeting an alert threshold only once, the alert triggercondition for the system user may be met only when an internal timeseries data point associated with the system user meets an alertthreshold for any time period, such as 5 consecutive minutes. Similarly,the alert trigger condition for the system user may be met only when aninternal time series data point associated with the system user meets analert threshold any number of times in any time period, such as bymeeting an alert threshold at least 7 times in any time period of 13consecutive minutes. Even though this example describes the time seriesdatabase system evaluating an internal time series data point associatedwith a system user on a minute-to-minute basis, the periodic evaluationperiod may be of any time duration, such as seconds or hours. While thisexample describes the time series database system evaluating whether asingle internal time series data point associated with a single systemuser meets a single alert trigger condition, the time series databasesystem may evaluate any number of internal time series data pointsassociated with any number of system users, and the time series databasesystem may evaluate whether each one of these internal time series datapoints associated with any number of system users meets any number ofalert trigger conditions.

If the internal time series data point associated with a system userdoes not meet the alert trigger condition for the system user, themethod 100 remains at block 106 to evaluate another alert triggercondition for the internal time series data point associated with thesystem user or to evaluate any other internal time series data pointassociated with any other system user, or the method 100 terminates ifthere are no more internal time series data points associated withsystem users to evaluate. If the internal time series data pointassociated with a system user meets the alert trigger condition for thesystem user, the method 100 proceeds to block 108 to reduce the systemuser's level of access.

If the internal time series data point associated with a system usermeets the alert trigger condition for the system user, the time seriesdatabase system reduces a level of access by the system user to the timeseries database system, block 108. For example and without limitation,this can include the time series database system suspending John Smith'saccess to the time series database system for one hour because theevaluation of the internal time series data point indicates that Smith's1,600 web service API calls for the 5 computer nodes meets the alerttrigger condition of 1,500 web service API calls per minute for the timeseries database system. The time series database system can detectsystem misuse or abuse by a system user, even when the system user isnot exceeding any subcomponent thresholds. For example, the multipletime series data points for the 5 computer nodes in the cluster may eachindicate that the system user John Smith has not exceeded the thresholdof 500 web service API calls for any of the 5 computer nodes, butSmith's total of 1,600 web service API calls made by the combination ofthe 5 computer nodes meets the alert trigger condition of 1,500 webservice API calls per minute for the time series database system as awhole.

Reducing a level of access by a system user to the time series databasesystem may be based on a reduction in the level of access by the systemuser to the time series database system and/or at least one of thesubsystems of the time series database system for a fixed time period oran indefinite period of time. For example, the time series databasesystem temporarily suspends John Smith's access to the time seriesdatabase system's subsystem for writing data to the time series databasesystem, but allows a continuation of John Smith's access to the timeseries database system's subsystem for reading data from the time seriesdatabase system. In another example, the time series database systemindefinitely suspends John Smith's access to the time series databasesystem.

Furthermore. reducing a level of access by a system user to the timeseries database system may be a reduction in the level of access bymultiple system users to the time series database system and/or at leastone of the subsystems of the time series database system. For example,each of the 5 computer nodes in a cluster will continue to allow writesto a node's discs until the discs are 95% full, based on the premisethat other nodes in the cluster have additional available disc space.Continuing this example, the time series database system indefinitelysuspends all users' access to write data to any node's discs because 90%of the combined disc space for all 5 nodes in the cluster is full, butthe time series database system allows all systems users to continuetheir read access from the 5 nodes' discs until a system administratorcan address the problem with the discs' storage capacity.

The time series database system may output an alert to inform a systemuser and/or a system administrator that the internal time series datapoint associated with the system user meets the alert trigger conditionfor the system user. For example, the time series database system mayoutput an alert email to inform John Smith and a system administratorthat Smith's 1,600 web service API calls per minute for the 5 computernodes exceeded 1,500 web service API calls per minute for the timeseries database system, and that the time series database systemtemporarily suspended Smith's access to the time series database system.

In another example, the time series database system outputs an alertemail to inform John Smith and a system administrator that Smith's 1,600web service API calls per minute for the 5 computer nodes exceeded 1,500web service API calls per minute for the time series database system,and that the time series database system temporarily reduced Smith'saccess to the time series database system to 750 web service API callsper minute. Although these examples describe the time series databasesystem communicating an alert notification via an email, the time seriesdatabase system may communicate an alert notification via anycombination of communications including emails, text messages, displayscreen updates, audible alarms, social network posts, tweets, writes todatabase records, etc. The system may also communicate an alertnotification to a computer system, even the time series database systemitself, in the form of control feedback, such that the computer systemreceiving the alert notification can take an action to mitigate animminent failure.

If the time series database system reduces a level of access by a systemuser to the time series database system, the time series database systemoptionally increases a level of access by the system user to time seriesdatabase system in response to a system administrator or a fixed timeperiod expiration, block 110. By way of example and without limitation,this can include the time series database system reinstating JohnSmith's previous level of access to the time series database system onehour after temporarily suspending Smith's access to the time seriesdatabase.

In another example, a system administrator receives John Smith's emailexplanation about Smith's 1,600 web service API calls per minute for the5 computer nodes, and responds by reinstating Smith's previous level ofaccess to the time series database system, thereby lifting the timeseries database system indefinite suspension of Smith's access to thetime series database system.

In yet another example, after the time series database system reinstatesJohn Smith's previous level of access to the time series database systemone hour after temporarily suspending Smith's access to the time seriesdatabase, the time series database system suspends John Smith's accessto the time series database system for six hours because Smith's 1,550web service API calls per minute for the 5 computer nodes exceeded 1,500web service API calls per minute for the time series database system ona second occasion.

The time series database system may progressively increase the severityof each successive level of access reduction for the same system userbased on historical records of the system user's level of accessreductions, whether or not each level of access reduction is based onmeeting the same alert trigger condition. For example, after a systemuser repeatedly exceeds alert trigger conditions, the time seriesdatabase system indefinitely suspends the system user, a level of accessreduction that can only be lifted by a system administrator, rather thansuspending the system user for the duration of a longer expiring timeperiod.

The method 100 may be repeated as desired. Although this disclosuredescribes the blocks 102-110 executing in a particular order, the blocks102-110 may be executed in a different order. In other implementations,each of the blocks 102-110 may also be executed in combination withother blocks and/or some blocks may be divided into a different set ofblocks.

FIG. 2 depicts an operational flow diagram illustrating a high leveloverview of a method 200 for a self-monitoring time series databasesystem which enforces usage policies based on monitoring rate of change.A time series database system optionally receives an alert triggercondition for a system user, wherein the system user is associated withmultiple time series data points corresponding to multiple subsystems ofthe time series database system, block 202. For example and withoutlimitation, this can include a system administrator for a time seriesdatabase system submitting an alert trigger condition of 1,500 webservice API calls per minute for the system user named John Smith forwhen Smith uses a cluster of 5 computer nodes, and alert triggerconditions of 500 web service API calls per minute for Smith for when heuses each of the 5 computer nodes.

Continuing this example, the time series database system identifies 5time series data points associated with the system user John Smith,which indicate Smith's web service API calls for the 5 computer nodeswithin the time series database system. Although this example describesthe time series database system identifying the multiple time seriesdata points that are associated with the alert trigger condition, asystem administrator may identify the multiple time series data pointsthat are associated with the alert trigger condition when submitting thealert trigger condition. While this example describes the time seriesdatabase system receiving and processing a single alert triggercondition for a single system user associated with multiple time seriesdata points corresponding to multiple subsystems of the time seriesdatabase system, the time series database system may receive and processany number of alert trigger conditions for any number of system users.

Even though the foregoing example describes the time series databasesystem receiving an alert trigger condition for a system user from asystem administrator, the time series database may also receive an alerttrigger condition for a system user from a configuration file. Forexample, upon startup, the time series database system initiallyreceives an alert trigger condition of 2,000 web service API calls perminute for each system user from a configuration file that waspre-configured prior to startup of the time series database system.Continuing this example, after months of operation, the time seriesdatabase system receives an alert trigger condition of 1,500 web serviceAPI calls per minute for each system user from a system administratorwho decided that the alert trigger condition of 2,000 web service APIcalls per minute for each system user was set too high for responding tothe corresponding alert notification in a timely manner.

After receiving the alert trigger condition for a system user associatedwith multiple time series data points, the time series database systemoptionally aggregates the multiple time series data points associatedwith a first time into a first internal time series data pointassociated with the system user and internal to the time series databasesystem, block 204. By way of example and without limitation, this caninclude the time series database system creating a global counter,aggregating the 5 time series data points, which indicate Smith's 1,200web service API calls for the 5 subsystems at 11:02 A.M., into theglobal counter, disabling subsystem aggregation to the global counter,copying the aggregated value of 1,200 in the global counter to atemporary data structure, resetting the global counter to zero, enablingsubsystem aggregation to the global counter, and persisting theaggregated value of 1,200 in the temporary data structure into a firstinternal time series data point for the system user John Smith in thetime series database system.

Although this example describes the time series database systemaggregating a single internal time series data point for one system userfrom multiple corresponding time series data points, the time seriesdatabase system may aggregate any number of internal time series datapoints for any number of system users from their multiple correspondingtime series data points While this example describes the time seriesdatabase system copying the aggregated value in the global counter to atemporary data structure, and then persisting the aggregated value inthe temporary data structure to an internal time series data point for asystem user, the time series database system may also copy theaggregated value in the global counter to an internal time series datapoint for a system user.

After aggregating the multiple time series data points associated withthe first time into the first internal time series data point associatedwith the system user, the time series database system optionallyevaluates whether the first internal time series data point associatedwith the system user meets the alert trigger condition, block 206. Inembodiments, this can include the time series database system evaluatingwhether the first internal time series data point aggregating the 5 timeseries data points, which indicate a total of Smith's 1,200 web serviceAPI calls for the 5 subsystems at 11:02 A.M., meets the alert triggercondition of 1,500 web service API calls per minute for Smith when usingthe time series database system.

Although the foregoing example describes an alert trigger conditionbased on an internal time series data point associated with a systemuser meeting an alert threshold only once, the alert trigger conditionmay be met when an internal time series data point associated with asystem user meets an alert threshold for any time period, such as 5consecutive minutes, or when an internal time series data pointassociated with a system user meets an alert threshold any number oftimes in any time period, such as by meeting an alert threshold at least7 times in any time period of 13 consecutive minutes. This exampledescribes the time series database system evaluating an internal timeseries data point associated with a system user on a minute-to-minutebasis. In some embodiments, the periodic evaluation period may be of anytime duration, such as seconds or hours. Further, this example describesthe time series database system evaluating whether a single internaltime series data point associated with a single system user meets asingle alert trigger condition. In some embodiments, the time seriesdatabase system may evaluate any number of internal time series datapoints associated with any number of system users, and then the timeseries database system may evaluate whether each one of these internaltime series data points associated with a system user meets any numberof alert trigger conditions.

If the first internal time series data point associated with the systemuser meets the alert trigger condition, the method 200 continues toblock 208 to reduce the level of access by the system user to the timeseries database system. If the first internal time series data pointassociated with the system user does not meet the alert triggercondition, the method 200 proceeds to block 210 to aggregate themultiple time series data points for the multiple subsystems into asecond internal time series data point associated with the system user.If the first internal time series data point associated with the systemuser meets the alert trigger condition, the time series database systemoptionally reduces the level of access by the system user to the timeseries database system, block 208. For example and without limitation,this can include the time series database system suspending John Smith'saccess to the time series database system for one hour because theevaluation of the first internal time series data point indicates thatSmith's 1,600 web service API calls for the 5 computer nodes meets thealert trigger condition of 1,500 web service API calls per minute forSmith when using the time series database system.

If the first internal time series data point associated with the systemuser does not meet the alert trigger condition, the time series databasesystem optionally aggregates the multiple time series data pointsassociated with a second time into a second internal time series datapoint associated with the system user and internal to the time seriesdatabase system, block 210. By way of example and without limitation,this can include the time series database system aggregating the 5 timeseries data points for the 5 subsystems, which indicate Smith's total of1,300 web service API calls for the 5 subsystems at 11:03 A.M., into asecond internal time series data point for John Smith. The time seriesdatabase system may aggregate the second internal time series data pointassociated with the system user similarly to how the time seriesdatabase system aggregated the first internal time series data pointassociated with the system user, as described above.

After aggregating the multiple time series data points associated withthe second time into the second internal time series data pointassociated with the system user, the time series database systemoptionally evaluates whether the second internal time series data pointassociated with the system user meets the alert trigger condition, block212. In embodiments, this can include the time series database systemevaluating whether the second internal time series data point indicatingSmith's 1,300 web service API calls for the 5 subsystems at 11:03 A.M.meets the alert trigger condition of 1,500 web service API calls perminute for John Smith. If the second internal time series data pointassociated with the system user meets the alert trigger condition, themethod 200 continues to block 214 to reduce a level of access by thesystem user to the time series database. If the second internal timeseries data point associated with the system user does not meet thealert trigger condition, the method 200 proceeds to block 216 tocalculate a projected internal time series data point associated withthe system user based on the first internal time series data pointassociated with the system user and the second internal time series datapoint associated with the system user.

If the second internal time series data point associated with the systemuser meets the alert trigger condition, the time series database systemoptionally reduces a level of access by the system user to the timeseries database, block 214. For example and without limitation, this caninclude the time series database system suspending John Smith's accessto the time series database system for one hour because the evaluationof the second internal time series data point indicates that Smith's1,600 web service API calls for the 5 computer nodes meets the alerttrigger condition of 1,500 web service API calls per minute for whenSmith uses the time series database system.

If the second internal time series data point associated with the systemuser does not meet the alert trigger condition, the time series databasesystem optionally calculates a projected internal time series data pointassociated with the system user based on the first internal time seriesdata point associated with the system user and the second internal timeseries data point associated with the system user, block 216. By way ofexample and without limitation, this can include the time seriesdatabase system calculating a projected internal time series data pointof 1,500 web service API calls per minute for John Smith at 11:05 A.M.based on 1,200 web service API calls per minute for John Smith at 11:02A.M. and 1,300 web service API calls per minute for John Smith at 11:03A.M.

Calculating the projected internal time series data point associatedwith the system user may be based on the first internal time series datapoint associated with the system user and/or the second internal timeseries data point associated with the system user meeting a datathreshold. For example, since the first internal time series datapoint's value of 1,200 web service API calls per minute for John Smithand the second internal time series data point's value of 1,300 webservice API calls per minute for John Smith are both above the 50%threshold of the alert trigger condition of 1,500 web service API callsper minute for John Smith, the time series database system calculatesthe projected internal time series data point for John Smith. In anotherexample, if the first internal time series data point's value of 600 webservice API calls per minute for John Smith and the second internal timeseries data point's value of 650 web service API calls per minute forJohn Smith are both below the 50% threshold of the alert triggercondition of 1,500 web service API calls per minute for John Smith, thetime series database system does not calculate the projected internaltime series data point for John Smith, thereby avoiding unnecessarycalculations

Although this example describes the time series database systemcalculating the projected internal time series data point associatedwith the system user based on only two internal time series data pointsassociated with the system user, the time series database system maycalculate the projected internal time series data point associated withthe system user based on any number of internal time series data pointsassociated with the system user. This example describes the time seriesdatabase system calculating the projected internal time series datapoint associated with the system user based on a liner projection. Insome embodiments, the time series database system may calculate theprojected internal time series data point associated with the systemuser based on any type of projection, such as exponential, logarithmic,or regression analysis, or combination thereof. Furthermore, thisexample describes the time series database system calculating theprojected internal time series data point associated with the systemuser based on meeting the alert trigger condition. In some embodiments,the time series database system may calculate the projected internaltime series data point based on a specified amount of time into thefuture, and then evaluate whether the projected internal time seriesdata point associated with the system user meets the alert triggercondition within a specified time threshold.

After calculating the projected internal time series data pointassociated with the system user, the time series database systemevaluates whether the projected internal time series data pointassociated with the system user meets the alert trigger condition, block218. In embodiments, this can include the time series database systemevaluating whether the projected internal time series data point of1,500 web service API calls per minute for John Smith at 11:05 A.M.meets the alert trigger condition of 1,500 web service API calls perminute for Smith. Evaluating whether the projected internal time seriesdata point associated with the system user meets the alert triggercondition may be based on meeting a time threshold. For example, if theprojected internal time series data point associated with the systemuser is projected to meet the alert trigger condition in 5 minutes, thetime series database system processes the projected internal time seriesdata point associated with the system user as having met the alerttrigger condition. In another example, if the projected internal timeseries data point associated with the system user is projected to meetthe alert trigger condition in 5 months, the time series database systemprocesses the projected internal time series data point associated withthe system user as having not met the alert trigger condition

If the projected internal time series data point associated with thesystem user meets the alert trigger condition, the method 200 continuesto block 220 to output a projected alert notification. If the projectedinternal time series data point associated with the system user does notmeet the alert trigger condition, the method 200 terminates.

If the projected internal time series data point associated with thesystem user meets the alert trigger condition, the time series databasesystem optionally outputs a projected alert notification associated withthe projected internal time series data point and the alert triggercondition, block 220. For example and without limitation, this caninclude the time series database system outputting an alert email toinform John Smith (and the system administrator) that Smith's webservice API calls for the 5 subsystems is projected to be 1,500 webservice API calls per minute at 11:05 A.M, which would result in asuspension of Smith's access to the time series database system.Although this example describes the time series database systemcommunicating a projected alert notification via an email, the timeseries database system may communicate a projected alert notificationvia any combination of communications including emails, text messages,display screen updates, audible alarms, social network posts, tweets,writes to database records, etc. Thus, the self-monitoring time seriesdatabase system of the present disclosure is advantageous in that itmonitors the system user's usage of the time series database systembased on projecting time series data that reflects multiple points intime.

The method 200 may be repeated as desired. Although this disclosuredescribes the blocks 202-220 executing in a particular order, the blocks202-220 may be executed in a different order. In other implementations,each of the blocks 202-220 may also be executed in combination withother blocks and/or some blocks may be divided into a different set ofblocks.

System Overview

FIG. 3 illustrates a block diagram of an environment 310 wherein anon-demand database service might be used. The environment 310 mayinclude user systems 312, a network 314, a system 316, a processorsystem 317, an application platform 318, a network interface 320, atenant data storage 322, a system data storage 324, program code 326,and a process space 328. In other embodiments, the environment 310 maynot have all of the components listed and/or may have other elementsinstead of, or in addition to, those listed above.

The environment 310 is an environment in which an on-demand databaseservice exists. A user system 312 may be any machine or system that isused by a user to access a database user system. For example, any of theuser systems 312 may be a handheld computing device, a mobile phone, alaptop computer, a work station, and/or a network of computing devices.As illustrated in FIG. 3 (and in more detail in FIG. 4) the user systems312 might interact via the network 314 with an on-demand databaseservice, which is the system 316.

An on-demand database service, such as the system 316, is a databasesystem that is made available to outside users that do not need tonecessarily be concerned with building and/or maintaining the databasesystem, but instead may be available for their use when the users needthe database system (e.g., on the demand of the users). Some on-demanddatabase services may store information from one or more tenants storedinto tables of a common database image to form a multi-tenant databasesystem (MTS). Accordingly, the “on-demand database service 316” and the“system 316” will be used interchangeably herein. A database image mayinclude one or more database objects. A relational database managementsystem (RDMS) or the equivalent may execute storage and retrieval ofinformation against the database object(s). The application platform 318may be a framework that allows the applications of the system 316 torun, such as the hardware and/or software, e.g., the operating system.In an embodiment, the on-demand database service 316 may include theapplication platform 318 which enables creation, managing and executingone or more applications developed by the provider of the on-demanddatabase service, users accessing the on-demand database service viauser systems 312, or third party application developers accessing theon-demand database service via the user systems 312.

The users of the user systems 312 may differ in their respectivecapacities, and the capacity of a particular user system 312 might beentirely determined by permissions (permission levels) for the currentuser. For example, where a salesperson is using a particular user system312 to interact with the system 316, that user system 312 has thecapacities allotted to that salesperson. However, while an administratoris using that user system 312 to interact with the system 316, that usersystem 312 has the capacities allotted to that administrator. In systemswith a hierarchical role model, users at one permission level may haveaccess to applications, data, and database information accessible by alower permission level user, but may not have access to certainapplications, database information, and data accessible by a user at ahigher permission level. Thus, different users will have differentcapabilities with regard to accessing and modifying application anddatabase information, depending on a user's security or permissionlevel.

The network 314 is any network or combination of networks of devicesthat communicate with one another. For example, the network 314 may beany one or any combination of a LAN (local area network), WAN (wide areanetwork), telephone network, wireless network, point-to-point network,star network, token ring network, hub network, or other appropriateconfiguration. As the most common type of computer network in currentuse is a TCP/IP (Transfer Control Protocol and Internet Protocol)network, such as the global internetwork of networks often referred toas the “Internet” with a capital “I,” that network will be used in manyof the examples herein. However, it should be understood that thenetworks that the one or more implementations might use are not solimited, although TCP/IP is a frequently implemented protocol.

The user systems 312 might communicate with the system 316 using TCP/IPand, at a higher network level, use other common Internet protocols tocommunicate, such as HTTP, FTP, AFS, WAP, etc. In an example where HTTPis used, the user systems 312 might include an HTTP client commonlyreferred to as a “browser” for sending and receiving HTTP messages toand from an HTTP server at the system 316. Such an HTTP server might beimplemented as the sole network interface between the system 316 and thenetwork 314, but other techniques might be used as well or instead. Insome implementations, the interface between the system 316 and thenetwork 314 includes load sharing functionality, such as round-robinHTTP request distributors to balance loads and distribute incoming HTTPrequests evenly over a plurality of servers. At least as for the usersthat are accessing that server, each of the plurality of servers hasaccess to the MTS' data; however, other alternative configurations maybe used instead.

In one embodiment, the system 316, shown in FIG. 3, implements aweb-based customer relationship management (CRM) system. For example, inone embodiment, the system 316 includes application servers configuredto implement and execute CRM software applications as well as providerelated data, code, forms, webpages and other information to and fromthe user systems 312 and to store to, and retrieve from, a databasesystem related data, objects, and Webpage content. With a multi-tenantsystem, data for multiple tenants may be stored in the same physicaldatabase object, however, tenant data typically is arranged so that dataof one tenant is kept logically separate from that of other tenants sothat one tenant does not have access to another tenant's data, unlesssuch data is expressly shared. In certain embodiments, the system 316implements applications other than, or in addition to, a CRMapplication. For example, the system 316 may provide tenant access tomultiple hosted (standard and custom) applications, including a CRMapplication. User (or third party developer) applications, which may ormay not include CRM, may be supported by the application platform 318,which manages creation, storage of the applications into one or moredatabase objects and executing of the applications in a virtual machinein the process space of the system 316.

One arrangement for elements of the system 316 is shown in FIG. 3,including the network interface 320, the application platform 318, thetenant data storage 322 for tenant data 323, the system data storage 324for system data 325 accessible to the system 316 and possibly multipletenants, the program code 326 for implementing various functions of thesystem 316, and the process space 328 for executing MTS system processesand tenant-specific processes, such as running applications as part ofan application hosting service. Additional processes that may execute onthe system 316 include database indexing processes.

Several elements in the system shown in FIG. 3 include conventional,well-known elements that are explained only briefly here. For example,each of the user systems 312 could include a desktop personal computer,workstation, laptop, PDA, cell phone, or any wireless access protocol(WAP) enabled device or any other computing device capable ofinterfacing directly or indirectly to the Internet or other networkconnection. Each of the user systems 312 typically runs an HTTP client,e.g., a browsing program, such as Microsoft's Internet Explorer browser,Netscape's Navigator browser, Opera's browser, or a WAP-enabled browserin the case of a cell phone, PDA or other wireless device, or the like,allowing a user (e.g., subscriber of the multi-tenant database system)of the user systems 312 to access, process and view information, pagesand applications available to it from the system 316 over the network314. Each of the user systems 312 also typically includes one or moreuser interface devices, such as a keyboard, a mouse, trackball, touchpad, touch screen, pen or the like, for interacting with a graphicaluser interface (GUI) provided by the browser on a display (e.g., amonitor screen, LCD display, etc.) in conjunction with pages, forms,applications and other information provided by the system 316 or othersystems or servers. For example, the user interface device may be usedto access data and applications hosted by the system 316, and to performsearches on stored data, and otherwise allow a user to interact withvarious GUI pages that may be presented to a user. As discussed above,embodiments are suitable for use with the Internet, which refers to aspecific global internetwork of networks. However, it should beunderstood that other networks can be used instead of the Internet, suchas an intranet, an extranet, a virtual private network (VPN), anon-TCP/IP based network, any LAN or WAN or the like.

According to one embodiment, each of the user systems 12 and all of itscomponents are operator configurable using applications, such as abrowser, including computer code run using a central processing unitsuch as an Intel Pentium® processor or the like. Similarly, the system316 (and additional instances of an MTS, where more than one is present)and all of their components might be operator configurable usingapplication(s) including computer code to run using a central processingunit such as the processor system 317, which may include an IntelPentium® processor or the like, and/or multiple processor units. Acomputer program product embodiment includes a machine-readable storagemedium (media) having instructions stored thereon/in which can be usedto program a computer to perform any of the processes of the embodimentsdescribed herein. Computer code for operating and configuring the system316 to intercommunicate and to process webpages, applications and otherdata and media content as described herein are preferably downloaded andstored on a hard disk, but the entire program code, or portions thereof,may also be stored in any other volatile or non-volatile memory mediumor device as is well known, such as a ROM or RAM, or provided on anymedia capable of storing program code, such as any type of rotatingmedia including floppy disks, optical discs, digital versatile disk(DVD), compact disk (CD), microdrive, and magneto-optical disks, andmagnetic or optical cards, nanosystems (including molecular memory ICs),or any type of media or device suitable for storing instructions and/ordata. Additionally, the entire program code, or portions thereof, may betransmitted and downloaded from a software source over a transmissionmedium, e.g., over the Internet, or from another server, as is wellknown, or transmitted over any other conventional network connection asis well known (e.g., extranet, VPN, LAN, etc.) using any communicationmedium and protocols (e.g., TCP/IP, HTTP, HTTPS, Ethernet, etc.) as arewell known. It will also be appreciated that computer code forimplementing embodiments can be implemented in any programming languagethat can be executed on a client system and/or server or server systemsuch as, for example, C, C++, HTML, any other markup language, Java™,JavaScript, ActiveX, any other scripting language, such as VBScript, andmany other programming languages as are well known may be used. (Java™is a trademark of Sun Microsystems, Inc.).

According to one embodiment, the system 316 is configured to providewebpages, forms, applications, data and media content to the user(client) systems 312 to support the access by the user systems 312 astenants of the system 316. As such, the system 316 provides securitymechanisms to keep each tenant's data separate unless the data isshared. If more than one MTS is used, they may be located in closeproximity to one another (e.g., in a server farm located in a singlebuilding or campus), or they may be distributed at locations remote fromone another (e.g., one or more servers located in city A and one or moreservers located in city B). As used herein, each MTS could include oneor more logically and/or physically connected servers distributedlocally or across one or more geographic locations. Additionally, theterm “server” is meant to include a computer system, includingprocessing hardware and process space(s), and an associated storagesystem and database application (e.g., OODBMS or RDBMS) as is well knownin the art. It should also be understood that “server system” and“server” are often used interchangeably herein. Similarly, the databaseobject described herein can be implemented as single databases, adistributed database, a collection of distributed databases, a databasewith redundant online or offline backups or other redundancies, etc.,and might include a distributed database or storage network andassociated processing intelligence.

FIG. 4 also illustrates the environment 310. However, in FIG. 4 elementsof the system 316 and various interconnections in an embodiment arefurther illustrated. FIG. 4 shows that the each of the user systems 312may include a processor system 312A, a memory system 312B, an inputsystem 312C, and an output system 312D. FIG. 4 shows the network 314 andthe system 316. FIG. 4 also shows that the system 316 may include thetenant data storage 322, the tenant data 323, the system data storage324, the system data 325, a User Interface (UI) 430, an ApplicationProgram Interface (API) 432, a PL/SOQL 434, save routines 436, anapplication setup mechanism 438, applications servers 400 ₁-400 _(N), asystem process space 402, tenant process spaces 404, a tenant managementprocess space 410, a tenant storage area 412, a user storage 414, andapplication metadata 416. In other embodiments, the environment 310 maynot have the same elements as those listed above and/or may have otherelements instead of, or in addition to, those listed above.

The user systems 312, the network 314, the system 316, the tenant datastorage 322, and the system data storage 324 were discussed above inreference to FIG. 3. Regarding the user systems 312, the processorsystem 312A may be any combination of one or more processors. The memorysystem 312B may be any combination of one or more memory devices, shortterm, and/or long term memory. The input system 312C may be anycombination of input devices, such as one or more keyboards, mice,trackballs, scanners, cameras, and/or interfaces to networks. The outputsystem 312D may be any combination of output devices, such as one ormore monitors, printers, and/or interfaces to networks. As shown by FIG.4, the system 316 may include the network interface 320 (of FIG. 3)implemented as a set of HTTP application servers 400, the applicationplatform 318, the tenant data storage 322, and the system data storage324. Also shown is the system process space 402, including individualtenant process spaces 404 and the tenant management process space 410.Each application server 400 may be configured to access tenant datastorage 322 and the tenant data 323 therein, and the system data storage324 and the system data 325 therein to serve requests of the usersystems 312. The tenant data 323 might be divided into individual tenantstorage areas 412, which can be either a physical arrangement and/or alogical arrangement of data. Within each tenant storage area 412, theuser storage 414 and the application metadata 416 might be similarlyallocated for each user. For example, a copy of a user's most recentlyused (MRU) items might be stored to the user storage 414. Similarly, acopy of MRU items for an entire organization that is a tenant might bestored to the tenant storage area 412. The UI 430 provides a userinterface and the API 432 provides an application programmer interfaceto the system 316 resident processes to users and/or developers at theuser systems 312. The tenant data and the system data may be stored invarious databases, such as one or more Oracle™ databases.

The application platform 318 includes the application setup mechanism438 that supports application developers' creation and management ofapplications, which may be saved as metadata into the tenant datastorage 322 by the save routines 436 for execution by subscribers as oneor more tenant process spaces 404 managed by the tenant managementprocess 410 for example. Invocations to such applications may be codedusing the PL/SOQL 434 that provides a programming language styleinterface extension to the API 432. A detailed description of somePL/SOQL language embodiments is discussed in commonly owned U.S. Pat.No. 7,730,478 entitled, METHOD AND SYSTEM FOR ALLOWING ACCESS TODEVELOPED APPLICATIONS VIA A MULTI-TENANT ON-DEMAND DATABASE SERVICE, byCraig Weissman, filed Sep. 21, 2007, which is incorporated in itsentirety herein for all purposes. Invocations to applications may bedetected by one or more system processes, which manages retrieving theapplication metadata 316 for the subscriber making the invocation andexecuting the metadata as an application in a virtual machine.

Each application server 400 may be communicably coupled to databasesystems, e.g., having access to the system data 325 and the tenant data323, via a different network connection. For example, one applicationserver 400 ₁ might be coupled via the network 314 (e.g., the Internet),another application server 400 _(N-1) might be coupled via a directnetwork link, and another application server 400 _(N) might be coupledby yet a different network connection. Transfer Control Protocol andInternet Protocol (TCP/IP) are typical protocols for communicatingbetween application servers 400 and the database system. However, itwill be apparent to one skilled in the art that other transportprotocols may be used to optimize the system depending on the networkinterconnect used.

In certain embodiments, each application server 400 is configured tohandle requests for any user associated with any organization that is atenant. Because it is desirable to be able to add and remove applicationservers from the server pool at any time for any reason, there ispreferably no server affinity for a user and/or organization to aspecific application server 400. In one embodiment, therefore, aninterface system implementing a load balancing function (e.g., an F5Big-IP load balancer) is communicably coupled between the applicationservers 400 and the user systems 312 to distribute requests to theapplication servers 400. In one embodiment, the load balancer uses aleast connections algorithm to route user requests to the applicationservers 400. Other examples of load balancing algorithms, such as roundrobin and observed response time, also can be used. For example, incertain embodiments, three consecutive requests from the same user couldhit three different application servers 400, and three requests fromdifferent users could hit the same application server 400. In thismanner, the system 316 is multi-tenant, wherein the system 316 handlesstorage of, and access to, different objects, data and applicationsacross disparate users and organizations.

As an example of storage, one tenant might be a company that employs asales force where each salesperson uses the system 316 to manage theirsales process. Thus, a user might maintain contact data, leads data,customer follow-up data, performance data, goals and progress data,etc., all applicable to that user's personal sales process (e.g., in thetenant data storage 322). In an example of a MTS arrangement, since allof the data and the applications to access, view, modify, report,transmit, calculate, etc., can be maintained and accessed by a usersystem having nothing more than network access, the user can manage hisor her sales efforts and cycles from any of many different user systems.For example, if a salesperson is visiting a customer and the customerhas Internet access in their lobby, the salesperson can obtain criticalupdates as to that customer while waiting for the customer to arrive inthe lobby.

While each user's data might be separate from other users' dataregardless of the employers of each user, some data might beorganization-wide data shared or accessible by a plurality of users orall of the users for a given organization that is a tenant. Thus, theremight be some data structures managed by the system 316 that areallocated at the tenant level while other data structures might bemanaged at the user level. Because an MTS might support multiple tenantsincluding possible competitors, the MTS should have security protocolsthat keep data, applications, and application use separate. Also,because many tenants may opt for access to an MTS rather than maintaintheir own system, redundancy, up-time, and backup are additionalfunctions that may be implemented in the MTS. In addition touser-specific data and tenant specific data, the system 316 might alsomaintain system level data usable by multiple tenants or other data.Such system level data might include industry reports, news, postings,and the like that are sharable among tenants.

In certain embodiments, the user systems 312 (which may be clientsystems) communicate with the application servers 400 to request andupdate system-level and tenant-level data from the system 316 that mayrequire sending one or more queries to the tenant data storage 322and/or the system data storage 324. The system 316 (e.g., an applicationserver 400 in the system 216) automatically generates one or more SQLstatements (e.g., one or more SQL queries) that are designed to accessthe desired information. The system data storage 324 may generate queryplans to access the requested data from the database.

Each database can generally be viewed as a collection of objects, suchas a set of logical tables, containing data fitted into predefinedcategories. A “table” is one representation of a data object, and may beused herein to simplify the conceptual description of objects and customobjects. It should be understood that “table” and “object” may be usedinterchangeably herein. Each table generally contains one or more datacategories logically arranged as columns or fields in a viewable schema.Each row or record of a table contains an instance of data for eachcategory defined by the fields. For example, a CRM database may includea table that describes a customer with fields for basic contactinformation such as name, address, phone number, fax number, etc.Another table might describe a purchase order, including fields forinformation such as customer, product, sale price, date, etc. In somemulti-tenant database systems, standard entity tables might be providedfor use by all tenants. For CRM database applications, such standardentities might include tables for Account, Contact, Lead, andOpportunity data, each containing pre-defined fields. It should beunderstood that the word “entity” may also be used interchangeablyherein with “object” and “table”.

In some multi-tenant database systems, tenants may be allowed to createand store custom objects, or they may be allowed to customize standardentities or objects, for example by creating custom fields for standardobjects, including custom index fields. U.S. Pat. No. 7,779,039, filedApr. 2, 2004, entitled “Custom Entities and Fields in a Multi-TenantDatabase System”, which is hereby incorporated herein by reference,teaches systems and methods for creating custom objects as well ascustomizing standard objects in a multi-tenant database system. Incertain embodiments, for example, all custom entity data rows are storedin a single multi-tenant physical table, which may contain multiplelogical tables per organization. It is transparent to customers thattheir multiple “tables” are in fact stored in one large table or thattheir data may be stored in the same table as the data of othercustomers.

While one or more implementations have been described by way of exampleand in terms of the specific embodiments, it is to be understood thatone or more implementations are not limited to the disclosedembodiments. To the contrary, it is intended to cover variousmodifications and similar arrangements as would be apparent to thoseskilled in the art. Therefore, the scope of the appended claims shouldbe accorded the broadest interpretation so as to encompass all suchmodifications and similar arrangements.

1. A system for a self-monitoring time series database system whichenforces usage policies, the apparatus comprising: one or moreprocessors; and a non-transitory computer readable medium storing aplurality of instructions, which when executed, cause the one or moreprocessors to: receive, by a time series database system, an alerttrigger condition for a system user, wherein the system user isassociated with a plurality of time series data points corresponding toa plurality of subsystems of the time series database system; aggregate,by the time series database system, the plurality of time series datapoints in an internal time series data point associated with the systemuser, the internal series data point being internal to the time seriesdatabase system; evaluate, by the time series database system, whetherthe internal time series data point associated with the system usermeets the alert trigger condition; reduce, by the time series databasesystem, a level of access by the system user to the time series databasesystem when the internal time series data point associated with thesystem user meets the alert trigger condition.
 2. The system of claim 1,wherein receiving the alert trigger condition comprises receiving thealert trigger condition from at least one of a system administrator anda configuration file.
 3. The system of claim 1, wherein the alerttrigger condition comprises at least one of a system thresholdassociated with the time series database system and a subsystemthreshold associated with at least one of the plurality of time seriesdata points corresponding to at least one of the plurality of subsystemsof the time series database system.
 4. The system of claim 1, whereinaggregating the plurality of time series data points in the internaltime series data point associated with the system user comprises:creating a global counter; aggregating the plurality of time series datapoints in the global counter; disabling subsystem aggregation to theglobal counter; copying a value in the global counter to a datastructure; resetting the global counter; enabling subsystem aggregationto the global counter; and persisting the value in the data structure tothe internal time series data point associated with the system user. 5.The system of claim 1, wherein reducing the level of access by thesystem user to the time series database system is based on a reductionin the level of access by the system user to at least one of the timeseries database system and at least one of the plurality of subsystemsof the time series database system for one of a fixed time period and anindefinite period of time.
 6. The system of claim 1, wherein reducingthe level of access by the system user to the time series databasesystem comprises a reduction in a level of access by a plurality ofsystem users to at least one of the time series database system and atleast one of the plurality of subsystems of the time series databasesystem.
 7. The system of claim 1, comprising further instructions, whichwhen executed, cause the one or more processors to increase a level ofaccess by the system user to the time series database system in responseto one of a system administrator and a fixed time period expiration. 8.A computer program product comprising computer-readable program code tobe executed by one or more processors when retrieved from anon-transitory computer-readable medium, the program code includinginstructions to: receive, by a time series database system, an alerttrigger condition for a system user, wherein the system user isassociated with a plurality of time series data points corresponding toa plurality of subsystems of the time series database system; aggregate,by the time series database system, the plurality of time series datapoints in an internal time series data point associated with the systemuser, internal time series data point being internal to the time seriesdatabase system; evaluate, by the time series database system, whetherthe internal time series data point associated with the system usermeets the alert trigger condition; reduce, by the time series databasesystem, a level of access by the system user to the time series databasesystem when the internal time series data point associated with thesystem user meets the alert trigger condition.
 9. The computer programproduct of claim 8, wherein receiving the alert trigger conditioncomprises receiving the alert trigger condition from at least one of asystem administrator and a configuration file.
 10. The computer programproduct of claim 8, wherein the alert trigger condition comprises atleast one of a system threshold associated with the time series databasesystem and a subsystem threshold associated with at least one of theplurality of time series data points corresponding to at least one ofthe plurality of subsystems of the time series database system.
 11. Thecomputer program product of claim 8, wherein aggregating the pluralityof time series data points in the internal time series data pointassociated with the system user comprises: creating a global counter;aggregating the plurality of time series data points in the globalcounter; disabling subsystem aggregation to the global counter; copyinga value in the global counter to a data structure; resetting the globalcounter; enabling subsystem aggregation to the global counter; andpersisting the value in the data structure to the internal time seriesdata point associated with the system user.
 12. The computer programproduct of claim 8, wherein reducing the level of access by the systemuser to the time series database system is based on a reduction in thelevel of access by the system user to at least one of the time seriesdatabase system and at least one of the plurality of subsystems of thetime series database system for one of a fixed time period and anindefinite period of time.
 13. The computer program product of claim 8,wherein reducing the level of access by the system user to the timeseries database system comprises a reduction in a level of access by aplurality of system users to at least one of the time series databasesystem and at least one of the plurality of subsystems of the timeseries database system.
 14. The computer program product of claim 8,wherein the program code comprises further instructions to increase alevel of access by the system user to the time series database system inresponse to one of a system administrator and a fixed time periodexpiration.
 15. A method for a self-monitoring time series databasesystem which enforces usage policies, the method comprising: receiving,by a time series database system, an alert trigger condition for asystem user, wherein the system user is associated with a plurality oftime series data points corresponding to a plurality of subsystems ofthe time series database system; aggregating, by the time seriesdatabase system, the plurality of time series data points in an internaltime series data point associated with the system user, the internaltime series data point being internal to the time series databasesystem; evaluating, by the time series database system, whether theinternal time series data point associated with the system user meetsthe alert trigger condition; reducing, by the time series databasesystem, a level of access by the system user to the time series databasesystem when the internal time series data point associated with thesystem user meets the alert trigger condition.
 16. The method of claim15, wherein receiving the alert trigger condition comprises receivingthe alert trigger condition from at least one of a system administratorand a configuration file.
 17. The method of claim 15, wherein the alerttrigger condition comprises at least one of a system thresholdassociated with the time series database system and a subsystemthreshold associated with at least one of the plurality of time seriesdata points corresponding to at least one of the plurality of subsystemsof the time series database system.
 18. The method of claim 15, whereinaggregating the plurality of time series data points in the internaltime series data point associated with the system user comprises:creating a global counter; aggregating the plurality of time series datapoints in the global counter; disabling subsystem aggregation to theglobal counter; copying a value in the global counter to a datastructure; resetting the global counter; enabling subsystem aggregationto the global counter; and persisting the value in the data structure tothe internal time series data point associated with the system user. 19.The method of claim 15, wherein reducing the level of access by thesystem user to the time series database system is based on a reductionin the level of access by the system user to at least one of the timeseries database system and at least one of the plurality of subsystemsof the time series database system for one of a fixed time period and anindefinite period of time.
 20. The method of claim 15, wherein reducingthe level of access by the system user to the time series databasesystem comprises a reduction in a level of access by a plurality ofsystem users to at least one of the time series database system and atleast one of the plurality of subsystems of the time series databasesystem.
 21. The method of claim 15, wherein the method further comprisesincreasing a level of access by the system user to the time seriesdatabase system in response to one of a system administrator and a fixedtime period expiration.